Unverified Commit a8559a67 authored by Robert Kimball's avatar Robert Kimball Committed by GitHub

Change behavior for bad/out-of-bounds OneHot values (#2534)

* address one-hot tests

* get backends passing unit tests

* disable OneHot test until it can be fixed
parent 13fc556e
...@@ -36,10 +36,14 @@ namespace ngraph ...@@ -36,10 +36,14 @@ namespace ngraph
void* arg, void* out, const Shape& out_shape, size_t one_hot_axis, int arena) void* arg, void* out, const Shape& out_shape, size_t one_hot_axis, int arena)
{ {
memset(out, 0, sizeof(ElementType) * shape_size(out_shape)); size_t element_count = shape_size(out_shape);
memset(out, 0, sizeof(ElementType) * element_count);
auto pos_raw = (static_cast<ElementType*>(arg))[0]; auto pos_raw = (static_cast<ElementType*>(arg))[0];
size_t pos = pos_raw; size_t pos = pos_raw;
(static_cast<ElementType*>(out))[pos] = 1; if (pos < element_count)
{
(static_cast<ElementType*>(out))[pos] = 1;
}
} }
template <typename ElementType> template <typename ElementType>
......
# one hot tests that expect exceptions
# Consider removing
one_hot_scalar_fp_nonint_in_3
one_hot_scalar_oob_in_3
one_hot_vector_1_barely_oob
one_hot_vector_1_far_oob
one_hot_vector_1_fp_nonint
backwards_maxpool_n2_c1_hw5_3x3_str2_max_pad1x2_2x3 backwards_maxpool_n2_c1_hw5_3x3_str2_max_pad1x2_2x3
backwards_batch_norm_training backwards_batch_norm_training
shape_of_scalar shape_of_scalar
......
...@@ -95,3 +95,4 @@ all_2x2x3_eliminate_dims_0_1_2 ...@@ -95,3 +95,4 @@ all_2x2x3_eliminate_dims_0_1_2
# GPU backend uses floats to implement these ops for int32 # GPU backend uses floats to implement these ops for int32
floor_int32 floor_int32
divide_int32 divide_int32
one_hot_scalar_oob_in_3
...@@ -27,8 +27,6 @@ namespace ngraph ...@@ -27,8 +27,6 @@ namespace ngraph
{ {
namespace reference namespace reference
{ {
// NOTE: Execution throws `std::range_error` if either a non-integral value or an out-of-bounds
// value is detected in the input tensor.
template <typename T> template <typename T>
void one_hot(const T* arg, void one_hot(const T* arg,
T* out, T* out,
...@@ -54,14 +52,14 @@ namespace ngraph ...@@ -54,14 +52,14 @@ namespace ngraph
if (std::floor(val) < val || std::floor(val) > val) if (std::floor(val) < val || std::floor(val) > val)
{ {
throw(std::range_error("One-hot: non-integral value in input")); continue;
} }
size_t one_hot_pos = static_cast<size_t>(val); size_t one_hot_pos = static_cast<size_t>(val);
if (one_hot_pos >= out_shape[one_hot_axis]) if (one_hot_pos >= out_shape[one_hot_axis])
{ {
throw(std::range_error("One-hot: value is out of category range")); continue;
} }
Coordinate one_hot_coord = inject(input_coord, one_hot_axis, one_hot_pos); Coordinate one_hot_coord = inject(input_coord, one_hot_axis, one_hot_pos);
......
...@@ -136,22 +136,13 @@ NGRAPH_TEST(${BACKEND_NAME}, one_hot_scalar_oob_in_3) ...@@ -136,22 +136,13 @@ NGRAPH_TEST(${BACKEND_NAME}, one_hot_scalar_oob_in_3)
// Create some tensors for input/output // Create some tensors for input/output
auto a = backend->create_tensor(element::i32, shape_a); auto a = backend->create_tensor(element::i32, shape_a);
copy_data(a, vector<int32_t>{3000000}); copy_data(a, vector<int32_t>{3});
auto result = backend->create_tensor(element::i32, shape_r); vector<int32_t> r_data(4);
auto result = backend->create_tensor(element::i32, shape_r, r_data.data());
try auto handle = backend->compile(f);
{ handle->call_with_validate({result}, {a});
auto handle = backend->compile(f); EXPECT_EQ(r_data[3], 0);
handle->call_with_validate({result}, {a});
}
catch (const std::exception& e)
{
EXPECT_EQ(e.what(), std::string("One-hot: value is out of category range"));
}
catch (...)
{
FAIL() << "Expected a std::out_of_range exception";
}
} }
NGRAPH_TEST(${BACKEND_NAME}, one_hot_vector_0) NGRAPH_TEST(${BACKEND_NAME}, one_hot_vector_0)
...@@ -213,49 +204,42 @@ NGRAPH_TEST(${BACKEND_NAME}, one_hot_vector_1_barely_oob) ...@@ -213,49 +204,42 @@ NGRAPH_TEST(${BACKEND_NAME}, one_hot_vector_1_barely_oob)
copy_data(a, vector<int32_t>{2, 1, 0, 0, 3, 2, 1, 0}); copy_data(a, vector<int32_t>{2, 1, 0, 0, 3, 2, 1, 0});
auto result = backend->create_tensor(element::i32, shape_r); auto result = backend->create_tensor(element::i32, shape_r);
try auto handle = backend->compile(f);
{ handle->call_with_validate({result}, {a});
auto handle = backend->compile(f); vector<int32_t> rv = read_vector<int32_t>(result);
handle->call_with_validate({result}, {a});
}
catch (const std::exception& e)
{
EXPECT_EQ(e.what(), std::string("One-hot: value is out of category range"));
}
catch (...)
{
FAIL() << "Expected a std::out_of_range exception";
}
}
NGRAPH_TEST(${BACKEND_NAME}, one_hot_vector_1_far_oob) EXPECT_EQ(rv[0], 0);
{ EXPECT_EQ(rv[1], 0);
Shape shape_a{8}; EXPECT_EQ(rv[2], 1);
auto A = make_shared<op::Parameter>(element::i32, shape_a);
Shape shape_r{8, 3};
auto r = make_shared<op::OneHot>(A, Shape{8, 3}, 1);
auto f = make_shared<Function>(r, ParameterVector{A});
auto backend = runtime::Backend::create("${BACKEND_NAME}"); EXPECT_EQ(rv[3], 0);
EXPECT_EQ(rv[4], 1);
EXPECT_EQ(rv[5], 0);
// Create some tensors for input/output EXPECT_EQ(rv[6], 1);
auto a = backend->create_tensor(element::i32, shape_a); EXPECT_EQ(rv[7], 0);
copy_data(a, vector<int32_t>{2, 1, 0, 0, 3000000, 2, 1, 0}); EXPECT_EQ(rv[8], 0);
auto result = backend->create_tensor(element::i32, shape_r);
try EXPECT_EQ(rv[9], 1);
{ EXPECT_EQ(rv[10], 0);
auto handle = backend->compile(f); EXPECT_EQ(rv[11], 0);
handle->call_with_validate({result}, {a});
} // These are undefined since value is out of bounds
catch (const std::exception& e) // EXPECT_EQ(rv[12], 0);
{ // EXPECT_EQ(rv[13], 0);
EXPECT_EQ(e.what(), std::string("One-hot: value is out of category range")); // EXPECT_EQ(rv[14], 0);
}
catch (...) EXPECT_EQ(rv[15], 0);
{ EXPECT_EQ(rv[16], 0);
FAIL() << "Expected a std::out_of_range exception"; EXPECT_EQ(rv[17], 1);
}
EXPECT_EQ(rv[18], 0);
EXPECT_EQ(rv[19], 1);
EXPECT_EQ(rv[20], 0);
EXPECT_EQ(rv[21], 1);
EXPECT_EQ(rv[22], 0);
EXPECT_EQ(rv[23], 0);
} }
NGRAPH_TEST(${BACKEND_NAME}, one_hot_matrix_0) NGRAPH_TEST(${BACKEND_NAME}, one_hot_matrix_0)
......
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